An introduction to automatic speaker recognition is presented in this chapter. The identifying characteristics of a person’s voice that make it possible to automatically identify a speaker are discussed. Subtasks such as speaker identiﬁcation, veriﬁcation, and detection are described. An overview of the techniques used to build speaker models as well as issues related to system performance are presented. Finally, a few selected applications of speaker recognition are introduced to demonstrate the wide range of applications of speaker recognition technologies.
The first panel of our program will
focus on the next generation of
scientists, “Science for All Students.”
We have three panelists participating in this
discussion: Drs. Leon Lederman, Richard Tapia,
and Marcia Linn.
Dr. Lederman is an internationally renowned
high-energy physicist, the Director Emeritus of
Fermi National Accelerator Laboratory in
Batavia, Illinois. He holds an appointment as
the Pritzker Professor of Science at Illinois
Institute of Technology in Chicago.
My foreign rights agents are the inestimable Danny and Heather Baror, and collectively
they have sold my books into literally dozens of countries and languages, helping to bring
my work to places I couldn't have dreamed of reaching on my own. They subcontract for
my agent Russell Galen, another inestimable personage without whom I would not have
attained anything like the dizzy heights that I enjoy today.
In this chapter, we will address the following questions: What do I need to know about the communication process to be an effective communicator? What do I need to know about the communication process to be an effective communicator? How can I use the different channels and patterns of communication to my advantage? How do contemporary managers use information technology to communicate more effectively? How can I be a better listener, reader, writer, and speaker?
Introduction -- THE CATEGORY OF MOOD
The meaning of this category is the attitude of the speaker, or writer towards the content of the
sentence. It is expressed
in the form of the verb.
There are three moods in English-the indicative mood, the imperative mood and the subjunctive mood.
The indicative mood indicates that what is said must be regarded as a fact, as something which has
occurred or is occurring at the moment of speaking or will occur in the future. It may denote actions with
different time-reference and different aspective characteristics.
We have analyzed 607 sentences of spontaneous human-computer speech data containing repairs, drawn from a total corpus of 10,718 sentences. We present here criteria and techniques for automatically detecting the presence of a repair, its location, and making the appropriate correction. The criteria involve integration of knowledge from several sources: pattern matching, syntactic and semantic analysis, and acoustics. INTRODUCTION Spontaneous spoken language often includes speech that is not intended by the speaker to be part of the content of the utterance. ...
By integrating syntactic and semantic processing, our parser (LAZY) is able to deterministically parse sentences which syntactically appear to be garden path sentences although native speakers do not need conscious reanalysis to understand them. LAZY comprises an extension to conceptual analysis which yields an explicit representation of syntactic information and a flexible interaction between semantic and syntactic knowledge. 1. INTRODUCTION The phenomenon we wish to model is the understanding of garden path sentences (GPs) by native speakers of English. ...